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How will Google scale its massive hiring ramp-up while maintaining its famously intricate screening process for ‘Googley’ employees? With an algorithm of course.

After months of interviewing their employees to decipher trends in personality and interests that mark Googlers, Google has ‘derived’ a complex hiring questionnaire. Google will begin using the surveys with all applicants this month. NYT (selections):

The questions range from the age when applicants first got excited about computers to whether they have ever tutored or ever established a nonprofit organization. The answers are fed into a series of formulas created by Google’s mathematicians that calculate a score — from zero to 100 — meant to predict how well a person will fit into its chaotic and competitive culture.

Until now, head hunters said, Google largely turned up its nose at engineers who had less than a 3.7 grade-point average… And it often would take two months to consider candidates, submitting them to more than half a dozen interviews. Unfortunately, most of the academic research suggests that the factors Google has put the most weight on — grades and interviews — are not an especially reliable way of hiring good people…

Last summer, Google asked every employee who had been working at the company for at least five months to fill out a 300-question survey.

Some questions were factual: What programming languages are you familiar with? What Internet mailing lists do you subscribe to? Some looked for behavior: Is your work space messy or neat? And some looked at personality: Are you an extrovert or an introvert? And some fell into no traditional category in the human resources world: What magazines do you subscribe to? What pets do you have?

“We wanted to cast a very wide net,” Mr. Bock said. “It is not unusual to walk the halls here and bump into dogs. Maybe people who own dogs have some personality trait that is useful.” [Plot spoiler: dog owning isn't the magic glue holding Google together.]…

The data from this initial survey was then compared with 25 separate measures of each employee’s performance. Again there were traditional yardsticks — the employee’s reviews, both by supervisors and peers, and their compensation — and some oddball ones.

Indeed, there was no single factor that seemed to find the top workers for every single job title. (And pet ownership did not seem to be a useful predictor of anything.) But Dr. Carlisle was able to create several surveys that he believed would help find candidates in several areas — engineering, sales, finance, and human resources.

7 thoughts on “Deriving Talent, Algorithmically”

I submitted some test apps last night, in hopes of trying out the new system, but there was no questionnaire yet. Don’t know if they did not start the out yet or what, but it sounds like a great way to hire people. I think we all know how bad an indicator interviews are…

Wow – and of course there will be the inevitable burgeoning industry of Job Application Optimizers that will try to game the Google algorithm, leading of course to the never-ending arms race between Google and Optimizers. I can’t wait for the chorus of complaints from unsuccessful job applicants every few months or so when Google adjusts the algorithm.

I guess everyone has this particular concept of algorithms when it comes to Google.But certainly I do not think that it uses algorithms to see the progress of its employees.
IMO it might be using algorithms to enhance the performance and creativity of its employees.What do you think?

John,
This is potentially good news.
For the past 100 years psychology has developed many techniques to assess personality and competence. These are more accurate and fairer than the interview lottery.

I hope Google is relying on these rather than concocting their own algorithms.